Doctoral Dissertations

Orcid ID

http://orcid.org/0000-0002-6029-7964

Date of Award

5-2020

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Energy Science and Engineering

Major Professor

Mitchel J. Doktycz

Committee Members

Constance Bailey, Steven Abel, Dale Pelletier, Jennifer Morrell-Falvey

Abstract

As our understanding of the microbial world has progressed, so too has the backlog of information and open questions generated from the thousands of uncharacterized proteins and metabolites with potential applications as biofuels, therapeutics, and biomaterials. To address this problem, new tools need to be developed in order to rapidly test and take advantage of uncharacterized proteins and metabolites. Cell-free systems have developed into a high-throughput and scalable tool for synthetic biology and metabolic engineering with applications across multiple disciplines. The work presented in this dissertation leverages cell-free systems as a conduit for the exploration of protein function and metabolite production using two complementary approaches. The first elucidates interaction networks associated with secondary metabolite production using a computationally assisted pathway description pipeline that employs bioinformatic searches of genome databases, structural modeling, and ligand-docking simulations to predict the gene products most likely to be involved in a metabolic pathway. In vitro reconstructions of the pathway are then modularly assembled and chemically verified in Escherichia coli lysates in order to differentiate between active and inactive pathways. The second takes a systems and synthetic biology approach to engineer Escherichia coli extracts capable of directing flux towards specific metabolites. Using growth and genome engineering-based methods, we produced cell-free proteomes capable of creating unconventional metabolic states with minimal impact on the cell in vivo. As a result of this work, we have significantly expanded our ability to use cell extracts outside of their native context to solve metabolic engineering problems and provide engineers new tools that can rapidly explore the functions of proteins and test novel metabolic pathways.

Files over 3MB may be slow to open. For best results, right-click and select "save as..."

Share

COinS